Data Analyst
פורסם אתמול · 86 מועמדים
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חולץ מתיאור המשרה · מתעדכן אוטומטית
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תיאור המשרה המלא
המשרה המקורית · נשמר לעיוןQodo is building the future of AI-powered software development. Our tools help engineering teams write better code, ship with more confidence, and move faster — without sacrificing quality. From intelligent code review to AI-driven test generation, Qodo sits at the intersection of developer tooling and cutting-edge AI. We're a fast-growing, product-led company trusted by thousands of developers and engineering teams worldwide.
We're looking for a Data Analyst to join our growing data team and help make analytics a core part of how we build. You'll work on the product-usage side of an AI product that thousands of developers rely on — understanding how teams adopt AI code review, which features drive value, and where we can make the experience better. It's a product-focused role at heart, reaching into business, operational, and cost metrics too, with room to shape how we work as the team grows.
• Be the go-to analyst for the product team — drive product analytics day to day: how developers use our AI features, plus retention and conversion funnels
• Turn raw product and usage data into clear, consistent metrics the team can trust
• Build and maintain the modeled data layer, so metrics live in one place and analysis is repeatable rather than rebuilt each time
• Build and maintain dashboards so teams can self-serve answers
• Run deep-dive analysis to surface opportunities and support product decisions and experimentation
• Extend into business and operational KPIs — conversion, churn, segmentation, customer value — and cost / unit-economics
• Take analyses from problem definition through to clear recommendations, not just reports
Requirements:
• 3+ years of industry experience as a Data, Product, Business, or BI Analyst, ideally in a developer-focused or technical B2B product
• AI-native: AI tools are a default part of how you work, and you build prompts, scripts, and small agents to automate the repetitive parts of your own analysis workflow
• Strong SQL and data modeling: you can move around a data warehouse independently, spot when a query that runs is still returning the wrong answer, and build clean, well-structured datasets that other people can rely on
• Experience with a product analytics tool (e.g. Mixpanel) or a BI tool, with proven experience building self-serve dashboards
• Strong communication and storytelling — you turn analysis into clear recommendations for non-technical stakeholders
• Solid business sense — comfortable moving between product metrics and broader business and operational KPIs
• Self-directed and comfortable with ambiguity — you can take a question from definition through to a clear answer with limited guidance, while working closely with a small team
• Fluent English, written and spoken
• Startup DNA — comfortable with fast iteration, shifting priorities, and wearing multiple hats
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